In chemical synthesis planning applications, the goal is to generate accurate and diverse sets of synthetic routes. However, data-driven computational applications can only be as good as the underpinning data.
Read this white paper to discover how collaboration between CAS and Bayer demonstrated the significant impact quality data can have on the predictive power of machine learning models.
